Error Resilient Video Coding Techniques Based on the Minimization of End-to-End Distortions

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DYNAMIC KEY BLOCK DECISION WITH SPATIO-TEMPORAL ANALYSIS FOR WYNER-ZIV VIDEO CODING

ABSTRACT Wyner-Ziv coding has been recognized as the most popular method up to now. For traditional WZC, side information is generated from intra-coded frames for use in the decoding of WZ frames. The unit for intra-coding is a frame and the distance between key-frames is kept constant. In this paper, the unit for intra-coding is a block, and the temporal distance between two consecutive key blocks can varying with time. A block is assigned a mode (WZ or intra-coded), depending on the result of spatio-temporal analysis, and encoded in an alternative manner. This strategy improves the overall coding efficiency, while maintaining a low encoder complexity. The performance gain can achieve up to 6 dB with respect to the traditional pixel-domain WZC

Multi-Focus Image Fusion and Depth Map Estimation Based on Iterative Region Splitting Techniques

In this paper, a multi-focus image stack captured by varying positions of the imaging plane is processed to synthesize an all-in-focus (AIF) image and estimate its corresponding depth map. Compared with traditional methods (e.g., pixel- and block-based techniques), our focus-based measures are calculated based on irregularly shaped regions that have been refined or split in an iterative manner, to adapt to different image contents. An initial all-focus image is first computed, which is then segmented to get a region map. Spatial-focal property for each region is then analyzed to determine whether a region should be iteratively split into sub-regions. After iterative splitting, the final region map is used to perform regionally best focusing, based on the Winner-take-all (WTA) strategy, i.e., choosing the best focused pixels from image stack. The depth image can be easily converted from the resulting label image, where the label for each pixel represents the image index from which the pixel with the best focus is chosen. Regions whose focus profiles are not confident in getting a winner of the best focus will resort to spatial propagation from neighboring confident regions. Our experiments show that the adaptive region-splitting algorithm outperforms other state-of-the-art methods or commercial software in synthesis quality (in terms of a well-known Q metric), depth maps (in terms of subjective quality), and processing speed (with a gain of 17.81~40.43%)

Automatic Multi-object Segmentation by Two-phase Snake Processing

[[abstract]]This paper presents a two-phase automatic snake algorithm for the segmentation of multiple objects from noisy or cluttered backgrounds. Traditional snake algorithms are often limited in their ability to process multiple objects and are required to have manually-drawn initial contours and fixed weighting parameters. Our algorithm features two phases: (1) the active-points phase and (2) the active-contours phase. In the first phase, grid points evenly distributed in the image are attracted and moved to form clusters near object boundaries. These clustered active points are then analyzed to obtain convex polygons as initial snake contours in the second phase, where a no-search movement scheme with space-varying weighting parameters is employed. Both the kinetics of active points and deformation of active contours accept our proposed adaptive gradient vector flow (AGVF) field as the contracting forces. Experiments show the stability of the AGVF field and good performance of our snake algorithm in segmenting multiple objects from noisy or cluttered backgrounds

Posture Monitoring for Health Care of Bedridden Elderly Patients Using 3D Human Skeleton Analysis via Machine Learning Approach

For bedridden elderly people, pressure ulcer is the most common and serious complication and could be prevented by regular repositioning. However, due to a shortage of long-term care workers, repositioning might not be implemented as often as required. Posture monitoring by using modern health/medical caring technology can potentially solve this problem. We propose a RGB-D camera system to recognize the posture of the bedridden elderly patients based on the analysis of 3D human skeleton which consists of articulated joints. Since practically most bedridden patients were covered with a blanket, only four 3D joints were used in our system. After the recognition of the posture, a warning message will be sent to the caregiver for assistance if the patient stays in the same posture for more than a predetermined period (e.g., two hours). Experimental results indicate that our proposed method is capable of achieving a high accuracy in posture recognition (above 95%). To the best of our knowledge, this application of using human skeleton analysis for patient care is novel. The proposed scheme is promising for clinical applications and will undertake an intensive test in health care facilities in the near future after redesigning a proper RGB-D (Red-Green-Blue-Depth) camera system. In addition, a desktop computer can be used for multi-point monitoring to reduce cost, since real-time processing is not required in this application